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Large Language Models Versus Physicians in Traditional Chinese Medicine: A Real-World Clinical Case Evaluation

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arXiv:2609.17544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical applications, yet their assessment for real-world traditional Chinese medicine (TCM) practice remains limited We constructed a clinical case library comprising 349 de-identified outpatient cases from 62 hospitals and evaluated 16 LLMs and a comparator cohort of 60 practicing TCM physicians using 60 representative cases selected from this library. Model outputs and physician reports were anonymized and scored by five senior TCM experts across nine diagnostic and therapeutic dimensions. Cutting-edge general-purpose LLMs achieved higher expert scores than the physician comparators, particularly for medical advice, treatment principles and selected diagnostic tasks. Howeve…

SourcearXiv Computational LinguisticsAuthor: Jiacheng Xie, Xiaoting Tang, Yang Yu, Jinpu Li, Shouli Li, Congcong Jing, Yantao Yang, Zhiyong Zhao, Ziyang Zhang, Qilin Song, Guanghui An, Dong Xu
Large Language Models Versus Physicians in Traditional Chinese Medicine: A Real-World Clinical Case Evaluation
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[Submitted on 15 Jul 2026]

Title:Large Language Models Versus Physicians in Traditional Chinese Medicine: A Real-World Clinical Case Evaluation

View a PDF of the paper titled Large Language Models Versus Physicians in Traditional Chinese Medicine: A Real-World Clinical Case Evaluation, by Jiacheng Xie and 11 other authors

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Abstract:Large language models (LLMs) are increasingly being explored for clinical applications, yet their assessment for real-world traditional Chinese medicine (TCM) practice remains limited We constructed a clinical case library comprising 349 de-identified outpatient cases from 62 hospitals and evaluated 16 LLMs and a comparator cohort of 60 practicing TCM physicians using 60 representative cases selected from this library. Model outputs and physician reports were anonymized and scored by five senior TCM experts across nine diagnostic and therapeutic dimensions. Cutting-edge general-purpose LLMs achieved higher expert scores than the physician comparators, particularly for medical advice, treatment principles and selected diagnostic tasks. However, prescription-level analyses revealed discrepancies in herb selection, dosage, and treatment strategy, and qualitative safety review identified hallucinations and undesirable template-driven outputs. These findings highlight the potential of LLMs for TCM decision support while underscoring the need for physician oversight, safety constraints and prospective clinical evaluation.

Subjects:

Computation and Language (cs.CL); Computers and Society (cs.CY)

Cite as: arXiv:2609.17544 [cs.CL]

(or arXiv:2609.17544v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.17544

arXiv-issued DOI via DataCite

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From: Jiacheng Xie [view email] [v1] Wed, 15 Jul 2026 03:18:48 UTC (6,006 KB)

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  • arXiv:2609.17544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical applications, yet their assessment for real-world traditi…

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